Interview-Specific Preparation
Comprehensive guides for each type of Meta Data Science interview
Overview
This section dives into the different types of interviews you can expect during the Meta data science interview process and provides targeted preparation strategies for each. While the exact structure can vary, these are common interview formats:
- Technical Skills Interview (Coding/SQL)
- Analytical Execution/Case Study Interview
- Analytical Reasoning/Product Sense Interview
- Behavioral Interview
Technical Skills Interview
This interview assesses your coding and problem-solving abilities using data. Expect SQL-heavy questions, but be prepared to use your preferred language (Python/R) for data manipulation and analysis tasks.
Key Topics: SQL proficiency, data manipulation with Pandas/dplyr, query optimization, analytical patterns
Analytical Execution Interview
This interview assesses your ability to conduct quantitative analysis, draw meaningful conclusions from data, and communicate your findings effectively.
Key Topics: Hypothesis generation, quantitative analysis, goal setting, KPIs, trade-off evaluation, A/B testing
Analytical Reasoning / Product Sense Interview
This interview assesses your product sense and ability to use data to inform product decisions. You'll work with ambiguous product questions and define relevant metrics.
Key Topics: Product sense frameworks, defining metrics, experiment design for social networks, North Star metrics, AARRR funnel
Behavioral Interview
The behavioral interview assesses your soft skills, how you've handled past situations, and how well you align with Meta's culture and values.
Key Topics: STAR method, Meta's values (Move Fast, Be Bold, Be Open, Focus on Impact), common behavioral questions